BackgroundAdvancing age is the primary selection criterion for community screening for atrial fibrillation (AF), with selection often restricted to those aged ≥65 years. If multivariable models were shown to have considerable additional value over age alone in predicting AF risk among younger individuals, AF screening could be expanded to patients with lower age, but with high AF risk as per a validated risk model.MethodsWe validated risk models CHARGE-AF (Cohorts for Heart and Aging Research in Genomic Epidemiology model for AF) and FHS-AF (Framingham Heart Study model for AF), and risk scores CHA₂DS₂-VASc and CHA₂DS₂-VA, and presented their predictive abilities for 5-year and 10-year AF risk versus that of age alone in a young Dutch population cohort (PREVEND) free from AF at baseline. We assessed discrimination by the C-statistic and calibration by the calibration plot and stratified Kaplan-Meier plot using survey-weighted Cox models.ResultsDuring 5-year and 10-year follow-up there were n=98 (2.46/1000 person-years) and n=249 (3.29/1000 person-years) new AF cases, respectively, among 8265 participants with mean age 49±13 years. CHARGE-AF and FHS-AF both showed good discrimination for 5-year and 10-year AF (C-statistic range 0.83–0.86) with accurate calibration for 5-year AF, but overestimation of 10-year AF risk in highest-risk individuals. CHA₂DS₂-VASc and CHA₂DS₂-VA relatively underperformed. Age alone showed similar discrimination to that of CHARGE-AF and FHS-AF both in the overall, young PREVEND cohort and in subgroups for lower age and lower stroke risk.ConclusionMultivariable models accurately discriminate for 5-year and 10-year AF risk among young European community-dwelling individuals. However, their additional discriminatory value over age alone was limited. Selection strategies for primary AF screening using multivariable models should not be expanded to younger individuals.